---
title: "Acala / Karura Income Statement"
output:
flexdashboard::flex_dashboard:
orientation: rows
vertical_layout: scroll
social: menu
source_code: embed
params:
network: Acala
---
```{css custom1, echo=FALSE}
.dataTables_scrollBody {
max-height: 100% !important;
}
```
```{r global, include=FALSE}
library(knitr)
knitr::opts_chunk$set(
message = FALSE,
warning = FALSE,
comment = "#>"
)
library(dygraphs)
library(kableExtra)
library(formattable)
library(lubridate)
library(flexdashboard)
library(DT)
library(subscanr)
library(formattable)
library(ghql)
x <- GraphqlClient$new()
# Helper function to concat
`%+%` <- function(a, b) paste0(a, b)
library(reticulate)
# use_python("/opt/homebrew/bin/python3.9")
network <- params$network
# define constants
if (tolower(network) == 'acala') {
dex_endpoint <- "https://api.subquery.network/sq/AcalaNetwork/acala-dex-subql"
nativeToken <- "ACA"
api_url = 'wss://acala-rpc-0.aca-api.network'
addr1 <- "23M5ttkmR6Kco5p3LFGKMpMv4zvLkKdUQWW1wGGoV8zDX3am"
addr2 <- "23M5ttkmR6KcnvsNJdmYTpLo9xfc54g8uCk55buDfiJPon69"
} else if (tolower(network) == 'karura') {
dex_endpoint <- "https://api.subquery.network/sq/AcalaNetwork/karura-dex-subql"
nativeToken <- "KAR"
api_url = 'wss://karura.polkawallet.io'
addr1 <- "qmmNufxeWaAUy17XBWGc1q4n2dkdxNS2dPkhtzCZRoExdAs"
addr2 <- "qmmNufxeWaAUp4SVa1Vi1owrzP1xhR6XKdorEcck17RF498"
}
# Get prices & blocks
method <- "tokenDailyData"
edges <- "tokenId price timestamp updateAtBlockId"
prices <- get_graph(dex_endpoint, method, edges, window = 31, filter = '')
prices[, block := as.numeric(updateAtBlockId) - 1]
prices[, date := as.Date(timestamp) - 1]
# prices <- merge(prices, tokens, by.x = "tokenId", by.y = "Token")
# prices[, adj := 10**as.numeric(decimals)]
prices[, price := as.numeric(price) / 10**18]
prices[, max_block := max(as.numeric(updateAtBlockId)), by = tokenId]
prices[, tokenId := fixToken(tokenId)]
# prices[tokenId=="KSM"]
# Get the max block for each date and feed that to the python code
minDate <- today() - 32
history <- prices[, max(block), by = date] %>%
setorder(date)
history[, blockDelta := V1 - shift(V1)]
block_history <- history[blockDelta > 5000 & date > minDate, V1]
write.csv(block_history, "history.csv", row.names = FALSE)
```
```{python, include=FALSE}
from substrateinterface import SubstrateInterface
import pandas as pd
import numpy as np
from datetime import date
history = pd.read_csv('history.csv', index_col = None)
block_history = history['x']
# block_id = block_history[30]
# pull in the balance for `acct` based on each block in `history`
def get_fees(url, acct, block_history):
data = []
try:
substrate = SubstrateInterface(url)
for j in block_history:
hash = substrate.get_block_hash(block_id = j)
timestamp = substrate.query(module='Timestamp',storage_function='Now',block_hash=hash).value
block = substrate.get_block_number(hash)
# result = substrate.query('System', 'Account', params = [acct], block_hash = hash)
# free = result.value['data']['free']
balance_info = substrate.get_runtime_state(
module='System',
storage_function='Account',
params=[acct],
block_hash=hash
).get('result')
balance = balance_info.get('data').get('free', 0) # / 10**12
outi = {"Block": block, "Time": timestamp, 'Balance': balance}
data.append(outi)
except Exception as e:
balance = None
return data
# url = 'wss://acala-rpc-0.aca-api.network'
url = r.api_url
acct = '23M5ttkmR6KcoTAAE6gcmibnKFtVaTP5yxnY8HF1BmrJ2A1i'
fees_api = get_fees(url, acct, block_history)
fees_api = pd.DataFrame(fees_api)
fees_api['Time'] = pd.to_datetime(fees_api['Time'],unit='ms')
```
```{r treasury, cache = TRUE, include=FALSE}
# Treasury account from Python API fees
fees <- py$fees_api %>%
as.data.table
fees[, Balance := as.numeric(Balance) / 10**12]
fees[, FeeIncome := Balance - shift(Balance, 1)]
fees[, date := as.Date(Time)]
# Stability fee
collaterParams <- getLoansCollateralParams_acala_loan(network)
collaterParams <- collaterParams[!duplicated(collateral.id), .(collateral.id, APR)]
if (network == 'Karura') {
pos <- getLoansDailyPositions_acala_loan(network, window = 31, staging = TRUE)
} else {
pos <- getLoansDailyPositions_acala_loan(network, window = 31, staging = TRUE)
}
pos <- pos[, .(timestamp, collateral.id, debitVolumeUSD, Date)]
pos <- merge(pos, collaterParams, by = "collateral.id", all.x = TRUE)
pos[, dailyAPR := APR / 365]
pos[, dailyFee := as.numeric(debitVolumeUSD) * dailyAPR]
fwrite(pos, file = network %+% "_stability_rawdata.csv")
dailyStability <- pos[, sum(dailyFee), by = Date] %>%
setnames("V1", "Stability_Fee_USD") %>%
setorder(Date)
fees <- merge(fees, dailyStability, by.x = 'date', by.y = 'Date', all.x = TRUE)
if (network == 'Karura') {
# get bad debt penalty from subquery
cdp2 <- getLiquidateUnsafeCDP_acala_loan(network, window = 31, staging = TRUE)
} else {
cdp2 <- getLiquidateUnsafeCDP_acala_loan(network, window = 31, staging = TRUE)
}
cdp2[, block.id := as.numeric(block.id)]
cdp3 <- cdp2[, .(Date, badDebitVolumeUSD)]
fwrite(cdp3, file = network %+% "_cdp_rawdata.csv")
cdp4 <- cdp3[, sum(as.numeric(badDebitVolumeUSD)) * .15, by = Date] %>%
setnames("V1", "CDP_Penalty_Fee_USD")
fees <- merge(fees, cdp4, by.x = 'date', by.y = 'Date', all.x = TRUE)
fees[is.na(CDP_Penalty_Fee_USD), CDP_Penalty_Fee_USD := 0]
liquidations <- cdp2[, .(block.id, timestamp, collateral.id, collateralVolumeUSD, badDebitVolumeUSD)]
# } else {
#
# # get bad debt penalty from subquery
# cdp2 <- getLiquidateUnsafeCDP_acala_loan(network, window = 31, staging = TRUE)
# cdp2[, block.id := as.numeric(block.id)]
# cdp3 <- cdp2[, .(Date, badDebitVolumeUSD)]
# fwrite(cdp3, file = network %+% "_cdp_rawdata.csv")
#
# cdp4 <- cdp3[, sum(as.numeric(badDebitVolumeUSD)) * .15, by = Date] %>%
# setnames("V1", "CDP_Penalty_Fee_USD")
# both <- merge(cdp_daily, cdp4, by.x = "date", by.y = "Date", all = TRUE)
#
# d <- list()
# for (i in 1:20) {
# cdp_rawdata <- get_subscan_events(nobs = 100, network = network, module = 'cdpengine', call = 'LiquidateUnsafeCDP', start_page = i, extract = TRUE)
# cdp <- cdp_rawdata$cdpengine_LiquidateUnsafeCDP
# cdp[, date := as.Date(time)]
# d[[i]] <- cdp[time >= minDate]
# if (min(cdp$date) < minDate) break
# }
# cdp <- rbindlist(d)
# cdp[, CurrencyId := fixToken(CurrencyId)]
# cdp[, block_num := as.numeric(block_num)]
# cdp[, BadDebtValue := as.numeric(BadDebtValue) / 10**12]
# cdp[, CollateralAmount := as.numeric(CollateralAmount) / 10**12]
# fwrite(cdp, file = network %+% "_cdp_rawdata.csv")
#
# cdp_daily <- cdp[, sum(as.numeric(BadDebtValue)) * .15, by = date] %>%
# setnames("V1", "CDP_Penalty_Fee_USD")
# fees <- merge(fees, cdp_daily, by.x = 'date', by.y = 'date', all.x = TRUE)
# liquidations <- cdp[, .(block_num, time, CurrencyId, CollateralAmount, BadDebtValue)]
#
# }
fees[is.na(CDP_Penalty_Fee_USD), CDP_Penalty_Fee_USD := 0]
fees <- tail(fees, 30)
fees7 <- tail(fees, 7)
sum30 <- fees[, .(sum(FeeIncome, na.rm = TRUE),
sum(Stability_Fee_USD, na.rm = TRUE),
sum(CDP_Penalty_Fee_USD, na.rm = TRUE))] %>%
setnames(c("V1", "V2", "V3"),
c("30D Sum FeeIncome_" %+% nativeToken, "30D Sum Stability_Fee_USD", "30D Sum CDP_Penalty_Fee_USD"))
sum7 <- fees7[, .(sum(FeeIncome, na.rm = TRUE),
sum(Stability_Fee_USD, na.rm = TRUE),
sum(CDP_Penalty_Fee_USD, na.rm = TRUE))] %>%
setnames(c("V1", "V2", "V3"),
c("7D Sum FeeIncome_" %+% nativeToken, "7D Sum Stability_Fee_USD", "7D Sum CDP_Penalty_Fee_USD"))
# test <- merge(cdp[, .(date, CurrencyId, block_num, BadDebtValue)],
# cdp2[, .(Date, collateral.id, block.id, badDebitVolumeUSD)],
# by.x = c('CurrencyId', 'block_num'),
# by.y = c('collateral.id', 'block.id'),
# all = TRUE)
# View(test)
# liquid staking fee
filter <- ' filter: {accountId: {equalTo: "' %+% addr1 %+% '"}}'
dat1 <- getDailyAccountBalance_acala_token(network, window = 31, filter = filter)
price <- prices[updateAtBlockId == max_block, .(tokenId, price)]
dat1 <- merge(dat1,
prices[, .(tokenId, timestamp, price)],
by = c("timestamp","tokenId"),
all.x = TRUE)
dat1[, balanceUSD := free * price]
data1 <- dat1[free > 1, .(tokenId, timestamp, free, price, balanceUSD)]
# builtin1 <- try(subscanr::get_subscan_account_tokens(network = network, addr))
# while (inherits(builtin1, "try-error")) {
# Sys.sleep(3)
# builtin1 <- try(subscanr::get_subscan_account_tokens(network, addr))
# }
# time <- as.POSIXct(builtin1$generated_at, origin = "1970-01-01", tz = 'UTC')
# data1 <- builtin1$data$builtin %>%
# as.data.table
# data1[, balance := as.numeric(balance) / 10**as.numeric(decimals)]
# price <- prices[updateAtBlockId == max_block, .(tokenId, price)]
# data1 <- merge(data1, price, by.x = "symbol", by.y = "tokenId", all.x = TRUE)
# data1[, balanceUSD := balance * price]
# data1[, .(symbol, balance, price, balanceUSD)]
# Stablecoin stability fee + liquidation fee, aUSD balance
filter <- ' filter: {accountId: {equalTo: "' %+% addr1 %+% '"}}'
dat2 <- getDailyAccountBalance_acala_token(network, window = 31, filter = filter)
price <- prices[updateAtBlockId == max_block, .(tokenId, price)]
dat2 <- merge(dat2,
prices[, .(tokenId, timestamp, price)],
by = c("timestamp","tokenId"),
all.x = TRUE)
dat2[, balanceUSD := free * price]
setorder(dat2, tokenId, timestamp)
data2 <- dat2[free > 1, .(tokenId, timestamp, free, price, balanceUSD)]
# addr <- "qmmNufxeWaAUp4SVa1Vi1owrzP1xhR6XKdorEcck17RF498"; network = "Karura"
# builtin2 <- try(subscanr::get_subscan_account_tokens(network, addr))
# while (inherits(builtin2, "try-error")) {
# Sys.sleep(3)
# builtin2 <- try(subscanr::get_subscan_account_tokens(network, addr))
# }
# time <- as.POSIXct(builtin2$generated_at, origin = "1970-01-01", tz = 'UTC')
# data2 <- builtin2$data$builtin %>%
# as.data.table
# data2[, balance := as.numeric(balance) / 10**as.numeric(decimals)]
# price <- prices[updateAtBlockId == max_block, .(tokenId, price)]
# data2 <- merge(data2, price, by.x = "symbol", by.y = "tokenId", all.x = TRUE)
# data2[, balanceUSD := balance * price]
# data2[, .(symbol, balance, price, balanceUSD)]
# It should have a section display the current holding and dollar value,
# last 7 day income, last 30 day income, some charts if you have time
```
# `r network` Income {.tabset}
Row
----
### 7D Fee Income
```{r sum7}
knitr::kable(sum7, escape = FALSE, format.args = list(big.mark = ",")) %>%
kable_styling()
```
Row
----
### 30D Fee Income
```{r sum30}
knitr::kable(sum30, escape = FALSE, format.args = list(big.mark = ",")) %>%
kable_styling()
dat <- fees[, .(date, FeeIncome, Stability_Fee_USD, CDP_Penalty_Fee_USD)]
main <- network %+% " Daily Fees"
dygraph(dat, main = main) %>%
dySeries("FeeIncome", stepPlot = TRUE, fill = TRUE)
rm(dat)
```
Row
----
### Daily Fee Data
```{r daily}
knitr::kable(fees, escape = FALSE, format.args = list(big.mark = ",")) %>%
kable_styling()
```
# `r network` Balances {.tabset}
Row
----
### Balance for account `r addr1`
```{r data1}
knitr::kable(data1[timestamp == max(timestamp)], escape = FALSE, format.args = list(big.mark = ",")) %>%
kable_styling()
dat <- data1[, .(timestamp, tokenId, balanceUSD)]
dat[, timestamp := as.Date(timestamp)]
us <- unique(dat$tokenId)
main <- network %+% " " %+% us[1] %+% " Treasury in " %+% addr1
dygraph(dat[tokenId == us[1], .(timestamp, balanceUSD)], main = main) %>%
dySeries("balanceUSD", stepPlot = TRUE, fill = TRUE)
if (length(us) > 1) {
main <- network %+% " " %+% us[2] %+% " Treasury in " %+% addr1
dygraph(dat[tokenId == us[2], .(timestamp, balanceUSD)], main = main) %>%
dySeries("balanceUSD", stepPlot = TRUE, fill = TRUE)
}
rm(dat)
```
Row
----
### Balance for account `r addr2`
```{r data2}
knitr::kable(data2[timestamp == max(timestamp)], escape = FALSE, format.args = list(big.mark = ",")) %>%
kable_styling()
dat <- data2[, .(timestamp, tokenId, balanceUSD)]
dat[, timestamp := as.Date(timestamp)]
us <- unique(dat$tokenId)
main <- network %+% " " %+% us[1] %+% " Treasury in " %+% addr2
dygraph(dat[tokenId == us[1], .(timestamp, balanceUSD)], main = main) %>%
dySeries("balanceUSD", stepPlot = TRUE, fill = TRUE)
if (length(us) > 1) {
main <- network %+% " " %+% us[2] %+% " Treasury in " %+% addr2
dygraph(dat[tokenId == us[2], .(timestamp, balanceUSD)], main = main) %>%
dySeries("balanceUSD", stepPlot = TRUE, fill = TRUE)
}
rm(dat)
```